Overview

Dataset statistics

Number of variables15
Number of observations252
Missing cells835
Missing cells (%)22.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory44.2 KiB
Average record size in memory179.7 B

Variable types

NUM14
CAT1

Reproduction

Analysis started2021-03-25 02:40:10.947288
Analysis finished2021-03-25 02:41:11.979641
Duration1 minute and 1.03 second
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

avg temp is highly correlated with min tempHigh correlation
min temp is highly correlated with avg tempHigh correlation
pop2019 is highly correlated with pop2020High correlation
pop2020 is highly correlated with pop2019High correlation
Safety Index is highly correlated with Crime IndexHigh correlation
Crime Index is highly correlated with Safety IndexHigh correlation
max temp has 6 (2.4%) missing values Missing
min temp has 6 (2.4%) missing values Missing
avg rainfall has 7 (2.8%) missing values Missing
Cost of Living pw has 94 (37.3%) missing values Missing
pop2020 has 35 (13.9%) missing values Missing
pop2019 has 35 (13.9%) missing values Missing
GrowthRate has 35 (13.9%) missing values Missing
area has 35 (13.9%) missing values Missing
Density has 35 (13.9%) missing values Missing
Crime Index has 122 (48.4%) missing values Missing
Safety Index has 122 (48.4%) missing values Missing
Health Care Index has 161 (63.9%) missing values Missing
Pollution Index has 142 (56.3%) missing values Missing
Country has unique values Unique

Variables

Country
Categorical

UNIQUE

Distinct count252
Unique (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Saint Kitts And Nevis
 
1
Ecuador
 
1
Angola
 
1
Nauru
 
1
U.S. Virgin Islands
 
1
Other values (247)
247
ValueCountFrequency (%) 
Saint Kitts And Nevis10.4%
 
Ecuador10.4%
 
Angola10.4%
 
Nauru10.4%
 
U.S. Virgin Islands10.4%
 
Belgium10.4%
 
Norway10.4%
 
Syria10.4%
 
Brunei10.4%
 
Western Sahara10.4%
 
Bhutan10.4%
 
Samoa10.4%
 
Bahrain10.4%
 
Monaco10.4%
 
Indian Ocean Island10.4%
 
Comoros10.4%
 
Kosovo10.4%
 
India10.4%
 
Montserrat10.4%
 
Lithuania10.4%
 
Bolivia10.4%
 
South Africa10.4%
 
Faroe Islands10.4%
 
Costa Rica10.4%
 
Mauritania10.4%
 
Other values (227)22790.1%
 
2021-03-25T15:41:12.185651image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length44
Median length8
Mean length9.888888889
Min length4

Overview of Unicode Properties

Unique unicode characters57
Unique unicode categories (?)5
Unique unicode scripts (?)2
Unique unicode blocks (?)2
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
a34413.8%
 
n2138.5%
 
i1947.8%
 
e1686.7%
 
r1385.5%
 
o1245.0%
 
1194.8%
 
s1084.3%
 
l1044.2%
 
t994.0%
 
d883.5%
 
u883.5%
 
c492.0%
 
h441.8%
 
S441.8%
 
m431.7%
 
g361.4%
 
I361.4%
 
A331.3%
 
b321.3%
 
M281.1%
 
C261.0%
 
B241.0%
 
y241.0%
 
T230.9%
 
Other values (32)26310.6%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter199580.1%
 
Uppercase Letter37415.0%
 
Space Separator1194.8%
 
Other Punctuation30.1%
 
Dash Punctuation1< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
S4411.8%
 
I369.6%
 
A338.8%
 
M287.5%
 
C267.0%
 
B246.4%
 
T236.1%
 
G225.9%
 
N184.8%
 
P154.0%
 
L133.5%
 
F112.9%
 
R112.9%
 
E112.9%
 
K102.7%
 
O82.1%
 
U82.1%
 
V71.9%
 
D71.9%
 
H61.6%
 
J41.1%
 
W41.1%
 
Z30.8%
 
Q10.3%
 
Y10.3%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
a34417.2%
 
n21310.7%
 
i1949.7%
 
e1688.4%
 
r1386.9%
 
o1246.2%
 
s1085.4%
 
l1045.2%
 
t995.0%
 
d884.4%
 
u884.4%
 
c492.5%
 
h442.2%
 
m432.2%
 
g361.8%
 
b321.6%
 
y241.2%
 
p201.0%
 
k180.9%
 
w140.7%
 
z130.7%
 
v130.7%
 
f80.4%
 
q50.3%
 
j40.2%
 
Other values (3)40.2%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
119100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.266.7%
 
'133.3%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-1100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin236995.1%
 
Common1234.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
a34414.5%
 
n2139.0%
 
i1948.2%
 
e1687.1%
 
r1385.8%
 
o1245.2%
 
s1084.6%
 
l1044.4%
 
t994.2%
 
d883.7%
 
u883.7%
 
c492.1%
 
h441.9%
 
S441.9%
 
m431.8%
 
g361.5%
 
I361.5%
 
A331.4%
 
b321.4%
 
M281.2%
 
C261.1%
 
B241.0%
 
y241.0%
 
T231.0%
 
G220.9%
 
Other values (28)23710.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
11996.7%
 
.21.6%
 
'10.8%
 
-10.8%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII249099.9%
 
None20.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
a34413.8%
 
n2138.6%
 
i1947.8%
 
e1686.7%
 
r1385.5%
 
o1245.0%
 
1194.8%
 
s1084.3%
 
l1044.2%
 
t994.0%
 
d883.5%
 
u883.5%
 
c492.0%
 
h441.8%
 
S441.8%
 
m431.7%
 
g361.4%
 
I361.4%
 
A331.3%
 
b321.3%
 
M281.1%
 
C261.0%
 
B241.0%
 
y241.0%
 
T230.9%
 
Other values (30)26110.5%
 

Most frequent None characters

ValueCountFrequency (%) 
ç150.0%
 
é150.0%
 

max temp
Real number (ℝ)

MISSING

Distinct count159
Unique (%)64.6%
Missing6
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean29.24548328830488
Minimum-3.388888889
Maximum44.72222222
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:12.403798image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum-3.388888889
5-th percentile19.84722222
Q127.33333333
median30.52777778
Q331.70833333
95-th percentile37.54166667
Maximum44.72222222
Range48.11111111
Interquartile range (IQR)4.375000003

Descriptive statistics

Standard deviation5.759087896
Coefficient of variation (CV)0.1969223021
Kurtosis5.31920254
Mean29.24548329
Median Absolute Deviation (MAD)1.888888885
Skewness-1.427360611
Sum7194.388889
Variance33.1670934
2021-03-25T15:41:12.613937image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
30.5555555693.6%
 
31.1111111183.2%
 
29.4444444452.0%
 
30.7222222241.6%
 
30.8333333341.6%
 
29.8888888941.6%
 
31.6666666741.6%
 
3041.6%
 
3141.6%
 
31.2777777841.6%
 
29.6111111141.6%
 
31.1666666741.6%
 
31.3888888931.2%
 
30.6111111131.2%
 
28.8333333331.2%
 
34.8888888931.2%
 
26.3888888931.2%
 
31.7777777831.2%
 
31.0555555631.2%
 
32.2222222231.2%
 
32.0555555631.2%
 
30.2222222220.8%
 
27.3333333320.8%
 
32.7222222220.8%
 
34.7222222220.8%
 
Other values (134)15360.7%
 
(Missing)62.4%
 
ValueCountFrequency (%) 
-3.38888888910.4%
 
7.88888888910.4%
 
8.33333333310.4%
 
12.2222222210.4%
 
13.1111111110.4%
 
13.510.4%
 
14.4444444410.4%
 
16.1111111110.4%
 
18.3888888910.4%
 
18.7777777810.4%
 
ValueCountFrequency (%) 
44.7222222210.4%
 
42.510.4%
 
40.6666666710.4%
 
40.2222222210.4%
 
4010.4%
 
39.6111111110.4%
 
38.7222222210.4%
 
38.4444444410.4%
 
38.3888888910.4%
 
38.2777777810.4%
 

min temp
Real number (ℝ)

HIGH CORRELATION
MISSING

Distinct count188
Unique (%)76.4%
Missing6
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean10.88414634132927
Minimum-30.77777778
Maximum26.66666667
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:12.981083image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum-30.77777778
5-th percentile-7.777777778
Q12.222222222
median14.75
Q320.88888889
95-th percentile23.54166667
Maximum26.66666667
Range57.44444445
Interquartile range (IQR)18.66666667

Descriptive statistics

Standard deviation11.62896143
Coefficient of variation (CV)1.06843119
Kurtosis0.04241873527
Mean10.88414634
Median Absolute Deviation (MAD)7.722222222
Skewness-0.8339571428
Sum2677.5
Variance135.2327439
2021-03-25T15:41:13.167053image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
22.7777777872.8%
 
22.2222222262.4%
 
23.3333333352.0%
 
21.8333333331.2%
 
19.0555555631.2%
 
21.3888888931.2%
 
21.1111111131.2%
 
20.3888888931.2%
 
21.6666666731.2%
 
24.4444444431.2%
 
-5.33333333331.2%
 
19.4444444431.2%
 
12.2222222220.8%
 
23.8888888920.8%
 
1920.8%
 
6.88888888920.8%
 
4.61111111120.8%
 
20.8888888920.8%
 
-7.77777777820.8%
 
17.3333333320.8%
 
9.88888888920.8%
 
-2.77777777820.8%
 
18.2222222220.8%
 
19.8888888920.8%
 
-3.77777777820.8%
 
Other values (163)17569.4%
 
(Missing)62.4%
 
ValueCountFrequency (%) 
-30.7777777810.4%
 
-26.7777777810.4%
 
-21.7222222210.4%
 
-18.9444444410.4%
 
-17.1111111110.4%
 
-15.6111111110.4%
 
-13.7222222210.4%
 
-12.2222222210.4%
 
-12.1666666710.4%
 
-11.6666666710.4%
 
ValueCountFrequency (%) 
26.6666666710.4%
 
24.7777777810.4%
 
24.6111111110.4%
 
24.4444444431.2%
 
24.3333333310.4%
 
23.9444444410.4%
 
23.8888888920.8%
 
23.7222222210.4%
 
23.6111111110.4%
 
23.5555555610.4%
 

avg temp
Real number (ℝ)

HIGH CORRELATION

Distinct count166
Unique (%)65.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.71031746009524
Minimum-13.88888889
Maximum28.5
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:13.353857image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum-13.88888889
5-th percentile5.616666667
Q113.94444444
median23.27777778
Q326.23611111
95-th percentile27.5
Maximum28.5
Range42.38888889
Interquartile range (IQR)12.29166667

Descriptive statistics

Standard deviation7.986407305
Coefficient of variation (CV)0.4051891767
Kurtosis0.529896522
Mean19.71031746
Median Absolute Deviation (MAD)3.861111115
Skewness-1.044214094
Sum4967
Variance63.78270164
2021-03-25T15:41:13.553826image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
27.22222222104.0%
 
2741.6%
 
25.5555555641.6%
 
26.1111111141.6%
 
27.541.6%
 
24.6666666741.6%
 
24.7222222241.6%
 
2541.6%
 
26.2777777831.2%
 
26.5555555631.2%
 
26.3888888931.2%
 
26.7777777831.2%
 
25.3888888931.2%
 
26.9444444431.2%
 
26.7222222231.2%
 
26.6666666731.2%
 
18.6111111120.8%
 
26.6111111120.8%
 
10.1111111120.8%
 
20.1666666720.8%
 
8.66666666720.8%
 
18.7222222220.8%
 
15.3888888920.8%
 
24.4444444420.8%
 
26.3333333320.8%
 
Other values (141)17268.3%
 
ValueCountFrequency (%) 
-13.8888888910.4%
 
-5.33333333310.4%
 
-0.94444444410.4%
 
-0.66666666710.4%
 
1.66666666710.4%
 
2.55555555610.4%
 
3.33333333310.4%
 
3.61111111110.4%
 
4.33333333310.4%
 
4.61111111110.4%
 
ValueCountFrequency (%) 
28.510.4%
 
28.3888888910.4%
 
28.3333333320.8%
 
28.2777777810.4%
 
2820.8%
 
27.8888888910.4%
 
27.8333333320.8%
 
27.6666666710.4%
 
27.541.6%
 
27.3888888910.4%
 

avg rainfall
Real number (ℝ≥0)

MISSING

Distinct count219
Unique (%)89.4%
Missing7
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean1213.6223673469387
Minimum50.8
Maximum3716.02
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:13.757273image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum50.8
5-th percentile187.96
Q1627.38
median1061.72
Q31666.24
95-th percentile2710.18
Maximum3716.02
Range3665.22
Interquartile range (IQR)1038.86

Descriptive statistics

Standard deviation773.958475
Coefficient of variation (CV)0.6377259482
Kurtosis0.3288647396
Mean1213.622367
Median Absolute Deviation (MAD)487.68
Skewness0.8510361977
Sum297337.48
Variance599011.721
2021-03-25T15:41:13.939049image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
510.5431.2%
 
114320.8%
 
754.3820.8%
 
541.0220.8%
 
556.2620.8%
 
695.9620.8%
 
1084.5820.8%
 
480.0620.8%
 
1036.3220.8%
 
876.320.8%
 
604.5220.8%
 
1501.1420.8%
 
1267.4620.8%
 
1092.220.8%
 
627.3820.8%
 
2461.2620.8%
 
1043.9420.8%
 
1363.9820.8%
 
1943.120.8%
 
1930.420.8%
 
574.0420.8%
 
187.9620.8%
 
177.820.8%
 
1701.820.8%
 
1061.7220.8%
 
Other values (194)19477.0%
 
(Missing)72.8%
 
ValueCountFrequency (%) 
50.810.4%
 
53.3410.4%
 
68.5810.4%
 
73.6610.4%
 
78.7410.4%
 
96.5210.4%
 
104.1410.4%
 
124.4610.4%
 
129.5410.4%
 
172.7210.4%
 
ValueCountFrequency (%) 
3716.0210.4%
 
3507.7410.4%
 
3472.1810.4%
 
3357.8810.4%
 
3309.6210.4%
 
3213.110.4%
 
3014.9810.4%
 
2857.510.4%
 
2839.7210.4%
 
2806.710.4%
 

Cost of Living pw
Real number (ℝ≥0)

MISSING

Distinct count158
Unique (%)100.0%
Missing94
Missing (%)37.3%
Infinite0
Infinite (%)0.0%
Mean688.668595441353
Minimum214.84594135586087
Maximum2997.941944167723
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:14.123668image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum214.8459414
5-th percentile267.825228
Q1398.4845653
median557.2123888
Q3939.3838381
95-th percentile1387.316646
Maximum2997.941944
Range2783.096003
Interquartile range (IQR)540.8992728

Descriptive statistics

Standard deviation401.0604482
Coefficient of variation (CV)0.5823707526
Kurtosis6.827432169
Mean688.6685954
Median Absolute Deviation (MAD)198.4591785
Skewness1.952641582
Sum108809.6381
Variance160849.4831
2021-03-25T15:41:14.314778image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
824.464691410.4%
 
769.796237610.4%
 
1515.94849410.4%
 
258.688415610.4%
 
377.511253410.4%
 
522.6352410.4%
 
1156.96015310.4%
 
437.476417210.4%
 
640.412275210.4%
 
226.01724110.4%
 
1050.424610.4%
 
445.12019910.4%
 
433.433970510.4%
 
537.699901210.4%
 
498.288871110.4%
 
286.093352610.4%
 
357.933185510.4%
 
260.455169810.4%
 
1378.90312510.4%
 
514.584010110.4%
 
408.15157510.4%
 
447.535753310.4%
 
717.062571410.4%
 
631.198767410.4%
 
1286.03621110.4%
 
Other values (133)13352.8%
 
(Missing)9437.3%
 
ValueCountFrequency (%) 
214.845941410.4%
 
226.01724110.4%
 
235.369937510.4%
 
244.69825210.4%
 
247.089437410.4%
 
258.688415610.4%
 
260.455169810.4%
 
261.37248810.4%
 
268.963946810.4%
 
277.339045710.4%
 
ValueCountFrequency (%) 
2997.94194410.4%
 
2194.58564910.4%
 
1682.415410.4%
 
1515.94849410.4%
 
1422.49442110.4%
 
1394.06661110.4%
 
1391.6202710.4%
 
1390.4220710.4%
 
1386.7686310.4%
 
1378.90312510.4%
 

pop2020
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct count217
Unique (%)100.0%
Missing35
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean35272.831069124426
Minimum1.357
Maximum1439323.7759999998
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:14.522676image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum1.357
5-th percentile27.8036
Q1555.987
median6486.205
Q323816.775
95-th percentile117266.1626
Maximum1439323.776
Range1439322.419
Interquartile range (IQR)23260.788

Descriptive statistics

Standard deviation140321.4118
Coefficient of variation (CV)3.978172648
Kurtosis85.00049697
Mean35272.83107
Median Absolute Deviation (MAD)6375.265
Skewness8.892459894
Sum7654204.342
Variance1.96900986e+10
2021-03-25T15:41:14.738665image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
59.1910.4%
 
4105.26710.4%
 
206139.58910.4%
 
33.69110.4%
 
11193.72510.4%
 
57.55910.4%
 
6524.19510.4%
 
9537.64510.4%
 
164689.38310.4%
 
15893.22210.4%
 
65.72210.4%
 
43851.04410.4%
 
2351.62710.4%
 
400.12410.4%
 
11326.61610.4%
 
21413.24910.4%
 
8278.72410.4%
 
98.34710.4%
 
18776.70710.4%
 
219.15910.4%
 
56.7710.4%
 
65273.51110.4%
 
23816.77510.4%
 
6948.44510.4%
 
3989.16710.4%
 
Other values (192)19276.2%
 
(Missing)3513.9%
 
ValueCountFrequency (%) 
1.35710.4%
 
1.62610.4%
 
3.4810.4%
 
4.99210.4%
 
5.79410.4%
 
10.82410.4%
 
11.23910.4%
 
11.79210.4%
 
15.00310.4%
 
17.56410.4%
 
ValueCountFrequency (%) 
1439323.77610.4%
 
1380004.38510.4%
 
331002.65110.4%
 
273523.61510.4%
 
220892.3410.4%
 
212559.41710.4%
 
206139.58910.4%
 
164689.38310.4%
 
145934.46210.4%
 
128932.75310.4%
 

pop2019
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct count217
Unique (%)100.0%
Missing35
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean34915.886013824886
Minimum1.34
Maximum1433783.686
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:14.933666image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum1.34
5-th percentile27.6256
Q1549.935
median6415.85
Q323310.715
95-th percentile115035.0442
Maximum1433783.686
Range1433782.346
Interquartile range (IQR)22760.78

Descriptive statistics

Standard deviation139329.8085
Coefficient of variation (CV)3.990441728
Kurtosis85.2045824
Mean34915.88601
Median Absolute Deviation (MAD)6303.847
Skewness8.905073137
Sum7576747.265
Variance1.941279554e+10
2021-03-25T15:41:15.130816image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
888.92710.4%
 
615.72910.4%
 
10047.71810.4%
 
69625.58210.4%
 
11333.48310.4%
 
10226.18710.4%
 
4974.98610.4%
 
33.8610.4%
 
42.38810.4%
 
97.11810.4%
 
30.0310.4%
 
329064.91710.4%
 
1355.98610.4%
 
10738.95810.4%
 
8519.37710.4%
 
11801.15110.4%
 
2759.62710.4%
 
215.05610.4%
 
33.70110.4%
 
77.14210.4%
 
127575.52910.4%
 
270625.56810.4%
 
1920.92210.4%
 
145872.25610.4%
 
6453.55310.4%
 
Other values (192)19276.2%
 
(Missing)3513.9%
 
ValueCountFrequency (%) 
1.3410.4%
 
1.61510.4%
 
3.37710.4%
 
4.98910.4%
 
5.82210.4%
 
10.75610.4%
 
11.43210.4%
 
11.64610.4%
 
14.86910.4%
 
17.54810.4%
 
ValueCountFrequency (%) 
1433783.68610.4%
 
1366417.75410.4%
 
329064.91710.4%
 
270625.56810.4%
 
216565.31810.4%
 
211049.52710.4%
 
200963.59910.4%
 
163046.16110.4%
 
145872.25610.4%
 
127575.52910.4%
 

GrowthRate
Real number (ℝ≥0)

MISSING

Distinct count165
Unique (%)76.0%
Missing35
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean1.0108603686635944
Minimum0.9753
Maximum1.0384
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:15.330168image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum0.9753
5-th percentile0.99552
Q11.0032
median1.0097
Q31.0181
95-th percentile1.0293
Maximum1.0384
Range0.0631
Interquartile range (IQR)0.0149

Descriptive statistics

Standard deviation0.01079959258
Coefficient of variation (CV)0.01068356512
Kurtosis-0.07937089564
Mean1.010860369
Median Absolute Deviation (MAD)0.0072
Skewness0.1453880134
Sum219.3567
Variance0.0001166311999
2021-03-25T15:41:15.545510image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1.014841.6%
 
1.003231.2%
 
1.004431.2%
 
1.006731.2%
 
1.001820.8%
 
1.003520.8%
 
1.029320.8%
 
1.007220.8%
 
1.023220.8%
 
1.009120.8%
 
1.018520.8%
 
1.000420.8%
 
1.024220.8%
 
1.014120.8%
 
1.025520.8%
 
1.012120.8%
 
1.012520.8%
 
1.005320.8%
 
1.000120.8%
 
1.013820.8%
 
1.007320.8%
 
1.007120.8%
 
1.009720.8%
 
1.008920.8%
 
1.002520.8%
 
Other values (140)16264.3%
 
(Missing)3513.9%
 
ValueCountFrequency (%) 
0.975310.4%
 
0.983110.4%
 
0.986510.4%
 
0.989210.4%
 
0.992610.4%
 
0.993410.4%
 
0.993920.8%
 
0.994110.4%
 
0.995220.8%
 
0.995610.4%
 
ValueCountFrequency (%) 
1.038410.4%
 
1.036810.4%
 
1.034710.4%
 
1.033210.4%
 
1.032710.4%
 
1.031210.4%
 
1.030510.4%
 
1.030210.4%
 
1.0310.4%
 
1.029810.4%
 

area
Real number (ℝ≥0)

MISSING

Distinct count217
Unique (%)100.0%
Missing35
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean612829.0414746543
Minimum2.0
Maximum17098242.0
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:15.789124image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile134
Q15765
median89342
Q3450295
95-th percentile2152969.2
Maximum17098242
Range17098240
Interquartile range (IQR)444530

Descriptive statistics

Standard deviation1819577.6
Coefficient of variation (CV)2.969143883
Kurtosis40.75346853
Mean612829.0415
Median Absolute Deviation (MAD)89081
Skewness5.905430961
Sum132983902
Variance3.310862641e+12
2021-03-25T15:41:16.035915image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
164819510.4%
 
54910.4%
 
37793010.4%
 
39075710.4%
 
5120910.4%
 
27296710.4%
 
3612510.4%
 
328759010.4%
 
7886510.4%
 
2889610.4%
 
23680010.4%
 
186210.4%
 
258610.4%
 
1158610.4%
 
175954010.4%
 
1217310.4%
 
92376810.4%
 
128521610.4%
 
61974510.4%
 
8353410.4%
 
46284010.4%
 
4903710.4%
 
82561510.4%
 
33080310.4%
 
47544210.4%
 
Other values (192)19276.2%
 
(Missing)3513.9%
 
ValueCountFrequency (%) 
210.4%
 
610.4%
 
1210.4%
 
2110.4%
 
2610.4%
 
3410.4%
 
5310.4%
 
5410.4%
 
6110.4%
 
9110.4%
 
ValueCountFrequency (%) 
1709824210.4%
 
998467010.4%
 
970696110.4%
 
937261010.4%
 
851576710.4%
 
769202410.4%
 
328759010.4%
 
278040010.4%
 
272490010.4%
 
238174110.4%
 

Density
Real number (ℝ≥0)

MISSING

Distinct count217
Unique (%)100.0%
Missing35
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean327.6227668202765
Minimum0.0262
Maximum19482.0
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:16.254830image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum0.0262
5-th percentile3.8308
Q132.0871
median91.0683
Q3220.6439
95-th percentile676.3262
Maximum19482
Range19481.9738
Interquartile range (IQR)188.5568

Descriptive statistics

Standard deviation1486.720023
Coefficient of variation (CV)4.537902045
Kurtosis132.5832265
Mean327.6227668
Median Absolute Deviation (MAD)67.8878
Skewness10.90340779
Sum71094.1404
Variance2210336.428
2021-03-25T15:41:16.446920image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
44.089810.4%
 
3.021410.4%
 
73.718610.4%
 
108.910210.4%
 
511.179610.4%
 
80.50710.4%
 
101.49310.4%
 
47.957810.4%
 
37.882310.4%
 
24.218210.4%
 
50.305910.4%
 
2.189710.4%
 
23.180510.4%
 
136.358810.4%
 
212.9310.4%
 
2145.322910.4%
 
103.140410.4%
 
18.076310.4%
 
135.538110.4%
 
56.306110.4%
 
1104.873410.4%
 
3.958210.4%
 
377.991610.4%
 
25.295710.4%
 
555.08210.4%
 
Other values (192)19276.2%
 
(Missing)3513.9%
 
ValueCountFrequency (%) 
0.026210.4%
 
0.277410.4%
 
2.06210.4%
 
2.189710.4%
 
3.021410.4%
 
3.276510.4%
 
3.291610.4%
 
3.481610.4%
 
3.548810.4%
 
3.641310.4%
 
ValueCountFrequency (%) 
1948210.4%
 
8175.122510.4%
 
5616.833310.4%
 
2145.322910.4%
 
1769.843310.4%
 
1393.582310.4%
 
1246.705910.4%
 
1157.518510.4%
 
1104.873410.4%
 
717.018910.4%
 

Crime Index
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct count127
Unique (%)97.7%
Missing122
Missing (%)48.4%
Infinite0
Infinite (%)0.0%
Mean44.68484615384616
Minimum12.29
Maximum84.25
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:16.635563image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum12.29
5-th percentile21.862
Q132.3575
median44.87
Q355.39
95-th percentile68.784
Maximum84.25
Range71.96
Interquartile range (IQR)23.0325

Descriptive statistics

Standard deviation15.32926781
Coefficient of variation (CV)0.3430529391
Kurtosis-0.4855484564
Mean44.68484615
Median Absolute Deviation (MAD)11.145
Skewness0.1892583225
Sum5809.03
Variance234.9864515
2021-03-25T15:41:16.822594image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
41.1920.8%
 
51.2220.8%
 
55.3920.8%
 
56.0410.4%
 
43.0110.4%
 
47.7410.4%
 
46.2310.4%
 
67.8510.4%
 
46.5610.4%
 
38.2610.4%
 
50.0310.4%
 
29.0910.4%
 
31.6610.4%
 
26.1510.4%
 
23.3510.4%
 
51.3110.4%
 
40.1310.4%
 
26.7210.4%
 
44.1410.4%
 
54.4110.4%
 
31.9710.4%
 
52.0810.4%
 
55.6410.4%
 
33.1310.4%
 
55.7710.4%
 
Other values (102)10240.5%
 
(Missing)12248.4%
 
ValueCountFrequency (%) 
12.2910.4%
 
15.2410.4%
 
15.3510.4%
 
20.2610.4%
 
20.7910.4%
 
21.3510.4%
 
21.7910.4%
 
21.9510.4%
 
22.6210.4%
 
23.3510.4%
 
ValueCountFrequency (%) 
84.2510.4%
 
80.2410.4%
 
77.0710.4%
 
76.3710.4%
 
74.7810.4%
 
70.9510.4%
 
68.8210.4%
 
68.7410.4%
 
68.0910.4%
 
67.8510.4%
 

Safety Index
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct count127
Unique (%)97.7%
Missing122
Missing (%)48.4%
Infinite0
Infinite (%)0.0%
Mean55.31515384615384
Minimum15.75
Maximum87.71
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:17.015882image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum15.75
5-th percentile31.216
Q144.61
median55.13
Q367.6425
95-th percentile78.138
Maximum87.71
Range71.96
Interquartile range (IQR)23.0325

Descriptive statistics

Standard deviation15.32926781
Coefficient of variation (CV)0.2771260087
Kurtosis-0.4855484564
Mean55.31515385
Median Absolute Deviation (MAD)11.145
Skewness-0.1892583225
Sum7190.97
Variance234.9864515
2021-03-25T15:41:17.234771image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
58.8120.8%
 
44.6120.8%
 
48.7820.8%
 
73.1410.4%
 
76.6510.4%
 
64.5810.4%
 
23.6310.4%
 
56.9910.4%
 
74.6910.4%
 
76.6210.4%
 
50.8110.4%
 
42.1110.4%
 
52.2610.4%
 
35.7810.4%
 
70.1110.4%
 
61.0710.4%
 
73.8510.4%
 
50.810.4%
 
31.1810.4%
 
70.2610.4%
 
33.3910.4%
 
60.6210.4%
 
67.8510.4%
 
53.0410.4%
 
22.9310.4%
 
Other values (102)10240.5%
 
(Missing)12248.4%
 
ValueCountFrequency (%) 
15.7510.4%
 
19.7610.4%
 
22.9310.4%
 
23.6310.4%
 
25.2210.4%
 
29.0510.4%
 
31.1810.4%
 
31.2610.4%
 
31.9110.4%
 
32.1510.4%
 
ValueCountFrequency (%) 
87.7110.4%
 
84.7610.4%
 
84.6510.4%
 
79.7410.4%
 
79.2110.4%
 
78.6510.4%
 
78.2110.4%
 
78.0510.4%
 
77.3810.4%
 
76.6510.4%
 

Health Care Index
Real number (ℝ≥0)

MISSING

Distinct count91
Unique (%)100.0%
Missing161
Missing (%)63.9%
Infinite0
Infinite (%)0.0%
Mean63.72549450549451
Minimum39.67
Maximum86.39
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:17.408639image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum39.67
5-th percentile45.19
Q156.11
median64.23
Q372.22
95-th percentile79.38
Maximum86.39
Range46.72
Interquartile range (IQR)16.11

Descriptive statistics

Standard deviation10.39635163
Coefficient of variation (CV)0.1631427377
Kurtosis-0.6481837785
Mean63.72549451
Median Absolute Deviation (MAD)8.14
Skewness-0.1448890211
Sum5799.02
Variance108.0841273
2021-03-25T15:41:17.583867image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
60.4310.4%
 
66.3810.4%
 
79.9610.4%
 
73.5810.4%
 
55.0110.4%
 
64.2310.4%
 
54.9710.4%
 
67.1210.4%
 
68.0210.4%
 
58.2810.4%
 
55.5710.4%
 
46.2110.4%
 
63.7210.4%
 
78.410.4%
 
75.7610.4%
 
48.8910.4%
 
68.5810.4%
 
70.8810.4%
 
70.7110.4%
 
73.7610.4%
 
42.710.4%
 
60.5210.4%
 
80.6810.4%
 
50.6610.4%
 
60.0910.4%
 
Other values (66)6626.2%
 
(Missing)16163.9%
 
ValueCountFrequency (%) 
39.6710.4%
 
42.710.4%
 
44.0210.4%
 
44.4410.4%
 
44.5710.4%
 
45.8110.4%
 
46.2110.4%
 
48.8910.4%
 
50.6610.4%
 
51.6210.4%
 
ValueCountFrequency (%) 
86.3910.4%
 
82.3410.4%
 
80.9910.4%
 
80.6810.4%
 
79.9610.4%
 
78.810.4%
 
78.410.4%
 
78.0810.4%
 
77.7110.4%
 
76.410.4%
 

Pollution Index
Real number (ℝ≥0)

MISSING

Distinct count108
Unique (%)98.2%
Missing142
Missing (%)56.3%
Infinite0
Infinite (%)0.0%
Mean57.602454545454535
Minimum11.86
Maximum92.2
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2021-03-25T15:41:17.774656image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum11.86
5-th percentile19.6005
Q140.635
median61.22
Q374.345
95-th percentile87.0845
Maximum92.2
Range80.34
Interquartile range (IQR)33.71

Descriptive statistics

Standard deviation21.03512245
Coefficient of variation (CV)0.3651775365
Kurtosis-0.8191765969
Mean57.60245455
Median Absolute Deviation (MAD)14.485
Skewness-0.439662382
Sum6336.27
Variance442.4763765
2021-03-25T15:41:18.124741image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
72.6220.8%
 
58.4220.8%
 
18.4410.4%
 
64.4810.4%
 
75.4410.4%
 
79.6210.4%
 
25.2810.4%
 
75.1210.4%
 
54.5310.4%
 
53.9310.4%
 
75.3910.4%
 
36.310.4%
 
50.4510.4%
 
20.410.4%
 
84.3510.4%
 
23.2710.4%
 
73.5710.4%
 
89.3510.4%
 
87.3510.4%
 
74.4410.4%
 
11.8610.4%
 
22.6510.4%
 
70.8510.4%
 
27.4810.4%
 
78.9610.4%
 
Other values (83)8332.9%
 
(Missing)14256.3%
 
ValueCountFrequency (%) 
11.8610.4%
 
16.2410.4%
 
18.1410.4%
 
18.4410.4%
 
19.0110.4%
 
19.210.4%
 
20.0910.4%
 
20.410.4%
 
22.6510.4%
 
23.2710.4%
 
ValueCountFrequency (%) 
92.210.4%
 
91.8410.4%
 
89.7710.4%
 
89.3510.4%
 
88.9810.4%
 
87.3510.4%
 
86.7610.4%
 
85.9210.4%
 
84.9110.4%
 
84.3510.4%
 

Interactions

2021-03-25T15:40:20.528835image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:20.998715image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:21.441109image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:21.837849image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:22.347859image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:22.821373image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:23.269718image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:23.746191image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:24.157132image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:24.646363image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:25.140303image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:25.602824image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:26.072899image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:26.543992image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:27.023226image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:27.466740image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:27.880837image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:28.362905image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:28.781413image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:29.197701image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:29.617102image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:29.931082image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:30.319638image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:30.758053image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:31.203987image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:31.506510image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:31.752176image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:32.016814image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:32.298566image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:32.594381image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:32.910633image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-03-25T15:40:33.186391image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
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Correlations

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Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-03-25T15:41:18.627368image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-03-25T15:41:18.891887image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-03-25T15:41:19.190867image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

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2021-03-25T15:41:11.873279image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Sample

First rows

Countrymax tempmin tempavg tempavg rainfallCost of Living pwpop2020pop2019GrowthRateareaDensityCrime IndexSafety IndexHealth Care IndexPollution Index
0Afghanistan35.388889-3.55555614.055556353.06261.37248838928.34638041.7541.0233652230.058.325776.3723.63NaN92.20
1Albania29.8888894.16666714.1666671229.36406.0398912877.7972880.9170.998928748.0100.212841.6458.3650.6678.59
2Algeria34.2777784.55555617.444444462.28258.68841643851.04443053.0541.01852381741.018.076351.8848.1255.0165.32
3American Samoa30.83333317.05555627.1111113507.74NaN55.19155.3120.9978199.0277.9497NaNNaNNaNNaN
4Andorra20.388889-5.0555565.6666671143.00739.04556177.26577.1421.0016468.0164.8333NaNNaNNaNNaN
5Angola28.72222211.16666721.277778993.14648.30083332866.27231825.2951.03271246700.025.527666.6333.37NaNNaN
6Anguilla31.11111123.33333327.6666671092.20NaN15.00314.8691.009091.0163.3956NaNNaNNaNNaN
7Antarctica-3.388889-30.777778-13.888889416.56NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
8Antigua And Barbuda30.05555622.33333326.444444739.14NaN97.92997.1181.0084442.0219.7240NaNNaNNaNNaN
9Thailand34.88888918.22222227.0555561615.44511.34225769799.97869625.5821.0025513120.0135.690639.3860.6278.0875.39

Last rows

Countrymax tempmin tempavg tempavg rainfallCost of Living pwpop2020pop2019GrowthRateareaDensityCrime IndexSafety IndexHealth Care IndexPollution Index
242Netherlands20.777778-0.2222229.555556754.381156.96015317134.87217097.1301.002241850.0408.533627.2272.7875.7625.28
243Venezuela30.55555619.11111124.6666671115.06444.19465228435.94028515.8290.9972916445.031.115784.2515.7539.6775.12
244United Kingdom19.8333331.4444449.333333754.381161.24936467886.01167530.1721.0053242900.0278.016445.2654.7474.9340.25
245Wake Island31.33333322.44444426.944444909.32NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
246Wallis And Futuna30.55555623.88888927.0000003309.62NaN11.23911.4320.9831142.080.5070NaNNaNNaNNaN
247West BankNaNNaN15.388889604.52NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
248Western Sahara29.88888913.00000021.00000068.58NaN597.339582.4631.0255266000.02.1897NaNNaNNaNNaN
249Yemen33.77777820.66666727.05555653.34392.61879929825.96429161.9221.0228527968.055.2343NaNNaNNaNNaN
250Zambia31.7222228.72222221.0000001043.94268.96394718383.95517861.0301.0293752612.023.732143.2256.78NaNNaN
251Zimbabwe29.0555567.16666719.666667764.54509.39904714862.92414645.4681.0148390757.037.479758.8841.12NaN74.44